Elastic scattering and total reaction cross sections of 6^{6}Li studied with a microscopic continuum discretized coupled channels model

We present a systematic study of $^{6}$Li elastic scattering and total reaction cross sections at incident energies around the Coulomb barrier within the continuum discretized coupled-channels (CDCC) framework, where $^{6}$Li is treated in an $\alpha$+$d$ two-body model. Collisions with $^{27}$Al, $^{64}$Zn, $^{138}$Ba and $^{208}$Pa are analyzed. The microscopic optical potentials (MOP) based on Skyrme nucleon-nucleon interaction for $\alpha$ and $d$ are adopted in CDCC calculations and satisfactory agreement with the experimental data is obtained without any adjustment on MOPs. For comparison, the $\alpha$ and $d$ global phenomenological optical potentials (GOP) are also used in CDCC analysis and a reduction no less than 50$\%$ on the surface imaginary part of deuteron GOP is required for describing the data. In all cases, the $^6$Li breakup effect is significant and provides repulsive correction to the folding model potential. The reduction on the GOP of deuteron reveals a strong suppression of the reaction probability of deuteron as a component of $^{6}$Li as compared with that of a free deuteron. A further investigation is made by taking the $d$ breakup process into account equivalently within the dynamic polarization potential approach and it shows that $d$ behaves like a tightly bound nucleus in $^{6}$Li induced reactions. We also compare the CDCC results with those calculated with a $^6$Li GOP and it shows that CDCC calculations provide a better reproduction for the elastic scattering angular distributions in the sub-barrier energy region and the total reaction cross sections at energies around the Coulomb barrier.Comment: 10 pages, 12 figure

Comprehensive analysis of the microbiome and metabolome in pus from pyogenic liver abscess patients with and without diabetes mellitus

IntroductionPyogenic liver abscess (PLA) patients combined with diabetes mellitus (DM) tend to have more severe clinical manifestations than without DM. The mechanism responsible for this phenomenon is not entirely clear. The current study therefore aimed to comprehensively analyze the microbiome composition and metabolome in pus from PLA patients with and without DM, to determine the potential reasons for these differences.MethodsClinical data from 290 PLA patients were collected retrospectively. We analyzed the pus microbiota using 16S rDNA sequencing in 62 PLA patients. In addition, the pus metabolomes of 38 pus samples were characterized by untargeted metabolomics analysis. Correlation analyses of microbiota, metabolites and laboratory findings were performed to identify significant associations.ResultsPLA patients with DM had more severe clinical manifestations than PLA patients without DM. There were 17 discriminating genera between the two groups at the genus level, among which Klebsiella was the most discriminating taxa. The ABC transporters was the most significant differential metabolic pathway predicted by PICRUSt2. Untargeted metabolomics analysis showed that concentrations of various metabolites were significantly different between the two groups and seven metabolites were enriched in the ABC transporters pathway. Phosphoric acid, taurine, and orthophosphate in the ABC transporters pathway were negatively correlated with the relative abundance of Klebsiella and the blood glucose level.DiscussionThe results showed that the relative abundance of Klebsiella in the pus cavity of PLA patients with DM was higher than those without DM, accompanied by changes of various metabolites and metabolic pathways, which may be associated with more severe clinical manifestations

Thrombocytopenia in Klebsiella pneumoniae liver abscess: a retrospective study on its correlation with disease severity and potential causes

ObjectiveThrombocytopenia is commonly associated with infectious diseases and serves as an indicator of disease severity. However, reports on its manifestation in conjunction with Klebsiella pneumoniae liver abscess (KPLA) are scarce. The present study sought to elucidate the correlation between thrombocytopenia and KPLA severity and delve into the etiological factors contributing to the incidence of thrombocytopenia.Materials and methodsA retrospective analysis of the clinical data from patients with KPLA admitted between June 2012 and June 2023 was performed. Baseline characteristics, biochemical assessments, therapeutic interventions, complications, and clinical outcomes were compared between patients with and without thrombocytopenia. To investigate the potential etiologies underlying thrombocytopenia, the association between platelet count reduction and thrombophlebitis was examined, with a particular focus on platelet consumption. Furthermore, bone marrow aspiration results were evaluated to assess platelet production anomalies.ResultsA total of 361 KPLA patients were included in the study, among whom 60 (17%) had concurrent thrombocytopenia. Those in the thrombocytopenia group exhibited significantly higher rates of thrombophlebitis (p = 0.042), extrahepatic metastatic infection (p = 0.01), septic shock (p = 0.024), admissions to the intensive care unit (p = 0.002), and in-hospital mortality (p = 0.045). Multivariate analysis revealed that thrombocytopenia (odds ratio, 2.125; 95% confidence interval, 1.114–4.056; p = 0.022) was independently associated with thrombophlebitis. Among the thrombocytopenic patients, eight underwent bone marrow aspiration, and six (75%) had impaired medullar platelet production. After treatment, 88.6% of thrombocytopenic patients (n = 47) demonstrated recovery in their platelet counts with a median recovery time of five days (interquartile range, 3–6 days).ConclusionsThrombocytopenia in patients with KPLA is indicative of increased disease severity. The underlying etiologies for thrombocytopenia may include impaired platelet production within the bone marrow and augmented peripheral platelet consumption as evidenced by the presence of thrombophlebitis

Cross-talk between PRMT1-mediated methylation and ubiquitylation on RBM15 controls RNA splicing

RBM15, an RNA binding protein, determines cell-fate specification of many tissues including blood. We demonstrate that RBM15 is methylated by protein arginine methyltransferase 1 (PRMT1) at residue R578 leading to its degradation via ubiquitylation by an E3 ligase (CNOT4). Overexpression of PRMT1 in acute megakaryocytic leukemia cell lines blocks megakaryocyte terminal differentiation by downregulation of RBM15 protein level. Restoring RBM15 protein level rescues megakaryocyte terminal differentiation blocked by PRMT1 overexpression. At the molecular level, RBM15 binds to pre-mRNA intronic regions of genes important for megakaryopoiesis such as GATA1, RUNX1, TAL1 and c-MPL. Furthermore, preferential binding of RBM15 to specific intronic regions recruits the splicing factor SF3B1 to the same sites for alternative splicing. Therefore, PRMT1 regulates alternative RNA splicing via reducing RBM15 protein concentration. Targeting PRMT1 may be a curative therapy to restore megakaryocyte differentiation for acute megakaryocytic leukemia

The giant panda gut harbors a high diversity of lactic acid bacteria revealed by a novel culturomics pipeline

Some lactic acid bacteria (LAB) can provide significant health benefits, which are critically important for the conservation of endangered animals, such as giant pandas. However, little is known about the diversity and culturability of LAB in the giant panda gut microbiota. To understand the roles of LAB in giant panda conservation, it is critical to culture bacterial strains of interest. In this study, we established a pipeline to culture bacterial strains using enrichment of target bacteria with different liquid media and growth conditions. Then, the strains were isolated in solid media to study their functions. Using 210 samples from the culture enrichment method and 138 culture-independent samples, we obtained 1120 amplicon sequencing variants (ASVs) belonging to Lactobacillales. Out of the 1120 ASVs, 812 ASVs from the culture enrichment approach were twofold more diverse than 336 ASVs from the culture-independent approach. Many ASVs of interest were not detected in the culture-independent approach. Using this pipeline, we isolated many relevant bacterial strains and established a giant panda gut bacteria strain collection that included strains with low-abundance in culture-independent samples and included most of the giant panda LAB described by other researchers. The strain collection consisted of 60 strains representing 35 species of 12 genera. Thus, our pipeline is powerful and provides guidance in culturing gut microbiota of interest in hosts such as the giant panda.This article is published as Zhang W, Zheng L, Xie J, Su X, Zhang M, Huang H, Schmitz-Esser S, Du S, Yang Y, Xie J, Zhang Q, Yu S, Guo Q, Wang H, Zhang L, Yang K, Hou R. 2024. The giant panda gut harbors a high diversity of lactic acid bacteria revealed by a novel culturomics pipeline. mSystems 9:e00520-24. https://doi.org/10.1128/msystems.00520-24. Copyright © 2024 Zhang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license

SBNN: A Searched Binary Neural Network for SAR Ship Classification

The synthetic aperture radar (SAR) for ocean surveillance missions requires low latency and light weight inference. This paper proposes a novel small-size Searched Binary Network (SBNN), with network architecture search (NAS) for ship classification with SAR. In SBNN, convolution operations are modified by binarization technologies. Both input feature maps and weights are quantized into 1-bit in most of the convolution computation, which significantly decreases the overall computational complexity. In addition, we propose a patch shift processing, which can adjust feature maps with learnable parameters at spatial level. This process enhances the performance by reducing the information irrelevant to the targets. Experimental results on the OpenSARShip dataset show the proposed SBNN outperforms both binary neural networks from computer vision and CNN-based SAR ship classification methods. In particular, SBNN shows a great advantage in computational complexity